Andreas Trügler

Details about my work and research.

Andreas Trügler

2 minute read

Physics at the nanoscale

Half a century ago it was Richard Feynman who first talked about the incredible possibilities if we investigate physics at the nanoscale (There’s Plenty of Room at the Bottom, 1959, Caltech).

It took nearly 20 years until this first concepts became reality. The discovery of fullerenes, carbon nanotubes and semiconducting nanostructures, the invention of the atomic force or scanning tunneling microscope are just a few milestones which lead to the fact, that nanotechnology is regarded as one of the key technologies of the 21st century.

The rapid advance of nanoscience in the last years led to a vast increase of research activities and inspired many scientists and research groups. The field of application is widespread, ranging from quantum optics, surface technology, and biochemistry, to also less obvious areas like medicine.

Nanoparticles and surface plasmons

Nanoparticles are small clusters with a diameter of about 10 to 100 nanometers and they consist of several thousands to millions of atoms. For such small objects the physical properties can differ appreciably compared to what they exhibit on a macroscale. One of the fascinating things is that quantum mechanical effects can be studied for these particles in a regime, where the transition from the micro- to the macrocosm takes place.

Boundary element method

The BEM is a powerful numerical tool to get solutions of Maxwell’s equations in the presence of arbitrarily shaped dielectrics. The problem is formulated in terms of surface integral equations which are calculated at the interfaces of the considered system. The electromagnetic field induced by the passage of an external electron or by an impinging light field is then calculated in terms of self-consistently obtained boundary charges and currents. These interface charges and currents act as sources of the induced electromagnetic field.

Research Interests


I'm a scientist and researcher working on privacy-preserving machine learning applications.